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Longitudinal Trajectories and Associated Baseline Predictors in Youths With Bipolar Spectrum Disorders
Boris Birmaher, M.D.; Mary Kay Gill, M.S.N.; David A. Axelson, M.D.; Benjamin I. Goldstein, M.D., Ph.D.; Tina R. Goldstein, Ph.D.; Haifeng Yu, M.S.; Fangzi Liao, M.S.; Satish Iyengar, Ph.D.; Rasim S. Diler, M.D.; Michael Strober, Ph.D.; Heather Hower, M.S.W.; Shirley Yen, Ph.D.; Jeffrey Hunt, M.D.; John A. Merranko, M.A.; Neal D. Ryan, M.D.; Martin B. Keller, M.D.
Am J Psychiatry 2014;:. doi:10.1176/appi.ajp.2014.13121577
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From the Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, Pittsburgh; the Department of Psychiatry, Nationwide Children’s Hospital and Ohio State College of Medicine, Columbus; the Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto Medical Center, Toronto; the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles; the Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, R.I.; the Department of Psychiatry, Bradley Hospital, East Providence, R.I., and the Department of Psychiatry, Butler Hospital, Providence.

Address correspondence to Dr. Birmaher (birmaherb@upmc.edu).

Copyright © 2014 by the American Psychiatric Association

Received December 03, 2013; Revised February 20, 2014; Accepted March 27, 2014.

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Objective  The authors sought to identify and evaluate longitudinal mood trajectories and associated baseline predictors in youths with bipolar disorder.

Method  A total of 367 outpatient youths (mean age, 12.6 years) with bipolar disorder with at least 4 years of follow-up were included. After intake, participants were interviewed on average 10 times (SD=3.2) over a mean of 93 months (SD=8.3). Youths and parents were interviewed for psychopathology, functioning, treatment, and familial psychopathology and functioning.

Results  Latent class growth analysis showed four different longitudinal mood trajectories: “predominantly euthymic” (24.0%), “moderately euthymic” (34.6%), “ill with improving course” (19.1%), and “predominantly ill” (22.3%). Within each class, youths were euthymic on average 84.4%, 47.3%, 42.8%, and 11.5% of the follow-up time, respectively. Multivariate analyses showed that better course was associated with higher age at onset of mood symptoms, less lifetime family history of bipolar disorder and substance abuse, and less history at baseline of severe depression, manic symptoms, suicidality, subsyndromal mood episodes, and sexual abuse. Most of these factors were more noticeable in the “predominantly euthymic” class. The effects of age at onset were attenuated in youths with lower socioeconomic status, and the effects of depression severity were absent in those with the highest socioeconomic status.

Conclusions  A substantial proportion of youths with bipolar disorder, especially those with adolescent onset and the above-noted factors, appear to be euthymic over extended periods. Nonetheless, continued syndromal and subsyndromal mood symptoms in all four classes underscore the need to optimize treatment.

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